SOTAVerified

Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

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Showing 1231–1240 of 1723 papers

TitleStatusHype
Semantic Detection of Potential Wind-borne Debris in Construction Jobsites: Digital Twining for Hurricane Preparedness and Jobsite Safety—0
Adversarial Scene Reconstruction and Object Detection System for Assisting Autonomous Vehicle—0
Monocular Depth Estimation with Sharp Boundary—0
Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation—0
Semantic Dense Reconstruction with Consistent Scene Segments—0
Referring Self-supervised Learning on 3D Point Cloud—0
D-Net: A Generalised and Optimised Deep Network for Monocular Depth EstimationCode0
Efficient Point Transformer for Large-scale 3D Scene Understanding—0
Audio-Visual Collaborative Representation Learning for Dynamic Saliency Prediction—0
Label-Attention Transformer with Geometrically Coherent Objects for Image CaptioningCode0
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified